SOTAVerified

Graph Generation

Graph Generation is an important research area with significant applications in drug and material designs.

Source: Graph Deconvolutional Generation

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 451–460 of 712 papers

TitleStatusHype
Analyzing Hong Kong's Legal Judgments from a Computational Linguistics point-of-view—0
Discovering Graph Generation Algorithms—0
Connector 0.5: A unified framework for graph representation learningCode0
KS-GNNExplainer: Global Model Interpretation Through Instance Explanations On Histopathology images—0
An Equivariant Generative Framework for Molecular Graph-Structure Co-DesignCode0
Devil's on the Edges: Selective Quad Attention for Scene Graph Generation—0
FairGen: Towards Fair Graph Generation—0
Taking A Closer Look at Visual Relation: Unbiased Video Scene Graph Generation with Decoupled Label LearningCode0
Decomposed Prototype Learning for Few-Shot Scene Graph Generation—0
FactReranker: Fact-guided Reranker for Faithful Radiology Report Summarization—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RNNStreetMover0.03—Unverified
2GraphRNNStreetMover0.02—Unverified
3GGT without CAStreetMover0.02—Unverified
4GGTStreetMover0.02—Unverified